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| Content Provider | IET Digital Library |
|---|---|
| Author | Liu, Shuo Li, Hongbo Zhang, Yun Zou, Bin |
| Abstract | This study presents a new approach to track the move-stop-move targets. In the presence of the radar Doppler blind area, a move-stop-move target may lead to track breakages, which has some adverse effects on estimating the number of targets in the surveillance area. The authors develop a mode switching-based multiple hypothesis tracking (MHT) method to solve this problem. In each association, MHT generates three types of hypotheses: moving and detected, moving and undetected and stopped. In the first two types of hypotheses, the target is in the mode of move and tracked with interacting multiple model (IMM)-extended Kalman filter (EKF) estimator, while in the third kind of hypotheses, the target is in the mode of stop and tracked by EKF with a stop model. The mode probabilities are calculated using the kinematic state statistics from the estimator and the Markov transfer probability of the target movement stage. The track discontinuity event in the classical log-likelihood ratio of MHT is modified as well. The results of simulation experiment show that the proposed MHT-based tracker outperforms the conventional MHT-based method when tracking move-stop-move target. |
| Starting Page | 6155 |
| Ending Page | 6159 |
| Page Count | 5 |
| Volume Number | 2019 |
| e-ISSN | 20513305 |
| Issue Number | Issue 19, Oct (2019) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/joe/2019/19 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0182 |
| Journal | The Journal of Engineering |
| Publisher | The Institution of Engineering and Technology |
| Publisher Date | 2019-05-30 |
| Access Restriction | Open |
| Rights License | Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
| Subject Keyword | Computer Vision And Image Processing Technique Conventional MHT-based Method Doppler Radar Filtering Method in Signal Processing Filtering Theory Kalman Filter Markov Processes MHT-based Tracker Mode Probabilities Mode Switching-based Multiple Hypothesis Tracking Method Move-stop-move Targets Movement Mode Multiple Hypothesis Method Multiple Model-extended Kalman Filter Estimator Nonlinear Filter Optical, Image And Video Signal Processing Probability Radar Doppler Blind Area Radar Equipment Radar Tracking Signal Processing And Detection Statistics Stop Model Surveillance Area System And Application Target Movement Stage Target Tracking Track Breakages Track Discontinuity Event Tracking Move-stop-move |
| Content Type | Text |
| Resource Type | Article |
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